Characteristics and influence factors of airborne bacterial communities in Changzhou's PM2.5 samples during spring
LIU Fei1, XUE Yin-gang1,2, TU Bo-wen3, WANG Li-ping1, ZHAO Ya-fang2, JIANG Xiao-dong1, XUE Ke1
1. School of Environmental and Safety Engineering, Changzhou University, Changzhou 213164, China;
2. Key Laboratory of Environmental Protection of Water Environment Biological Monitoring of Jiangsu Province, Changzhou Environmental Monitoring Center, Changzhou 213001, China;
3. Changzhou Centers for Disease Control and Prevention, Changzhou 213022, China
In order to investigate the characteristics of the airborne bacterial community in Changzhou's PM2.5samplesduring spring, the 16S rRNA gene of bacterial in PM2.5 sampleswas studied by high-throughput sequencing. 600150sequences obtained could be divided into 1890~6519 OTUs of each sample at 97% similarity level. The Coverage index of the samples was high and could accurately represent the airborne bacterial community in the samples. Species annotation results indicated that there were 11bacterial phyla, 14bacterial classes, 12bacterial genera with relative abundance greater than 1% in Changzhou's PM2.5 samples during spring. Proteobacteria, Bacteroidetes and Firmicutes were the top 3dominant phyla, accounting for 80.88% of the total gene abundance. At the genus level, Chroococcidiopsis (6.03%), Rubellimicrobium (5.95%), Microcystis (4.86%) and Sphingomonas (3.16%) were predominant, but the proportion of gene sequences that failed to be classified was up to 81.11%. Based on the source analysis of bacterial community composition in PM2.5, it was found that the environmental sources of bacteria in Changzhou's PM2.5 samples during spring were varied, and the main environmental source might be fresh water, followed by soil, plants and anthropogenic sources. The results of redundancy analysis (RDA) for the relationship between environmental factors and bacterial community showed that NH4+, NO3-, O3, SO42-, OC, air pressure and CO were the main environmental factors affecting the bacterial community in Changzhou's PM2.5 samplesduring spring. At the same time, varied environmental factors had different effects on bacterial groups.
Xu Q, Li X, Wang S, et al. Fine particulate air pollution and hospital emergency room visits for respiratory disease in urban areas in Beijing, China, in 2013[J]. Plos One, 2016,11(4):e0153099.
Ye Z L, Li Q, Liu J S, et al. Investigation of submicron aerosol characteristics in Changzhou, China:Composition, source, and comparison with co-collected PM2.5[J]. Chemosphere, 2017,183:176-185.
Tan J H, Zhang L M, Zhou X M, et al. Chemical characteristics and source apportionment of PM2.5 in Lanzhou, China[J]. Science of the Total Environment, 2017,601-602:1743-1752.
[8]
Rogula-Kozlowska W. Size-segregated urban particulate matter:mass closure, chemical composition, and primary and secondary matter content[J]. Air Quality Atmosphere & Health, 2016,9(5):533-550.
[9]
Cao S J, Kong X R, Li L Y, et al. An investigation of the PM2.5 and NO2 concentrations and their human health impacts in the metro subway system of Suzhou, China[J]. Environmental Science:Processes & Impacts, 2017,19(5):666-675.
[10]
Bari M A, Kindzierski W B. Ambient fine particulate matter (PM2.5) in Canadian oil sands communities:Levels, sources and potential human health risk[J]. Science of the Total Environment, 2017,595:828-838.
[11]
Sun Y J, Wang T Y, Peng X W, et al. Bacterial community compositions in sediment polluted by perfluoroalkyl acids (PFAAs) using Illumina high-throughput sequencing[J]. Environmental Science & Pollution Research, 2016,23(11):10556-10565.
[12]
Zhang W, Chen L, Zhang R, et al. High throughput sequencing analysis of the joint effects of BDE209-Pb on soil bacterial community structure[J]. Journal of Hazardous Materials, 2016,301:1-7.
Adams R I, Miletto M, Lindow S E, et al. Airborne bacterial communities in residences:similarities and differences with fungi[J]. Plos One, 2014,9(3):e91283.
Cao C, Jiang W J, Wang B Y, et al. Inhalable microorganisms in Beijing's PM2.5 and PM10 pollutants during a severe smog event[J]. Environmental Science & Technology, 2014,48(3):1499-1507.
[17]
Zhang J Y, Ding X, Guan R, et al. Evaluation of different 16S rRNA gene V regions for exploring bacterial diversity in a eutrophic freshwater lake[J]. Science of the Total Environment, 2017,618:1254-1267.
[18]
Desantis T Z, Hugenholtz P, Larsen N, et al. Greengenes:chimera-checked 16S rRNA gene database and workbenchcompatible in ARB[J]. Applied & Environmental Microbiology, 2006,72(7):5069-5072.
[19]
Caporaso J G, Kuczynski J, Stombaugh J, et al. QⅡME allows analysis of high-throughput community sequencing data[J]. Nature Methods, 2010,7(5):335-336.
[20]
Ter-Braak C J F, Šmilauer P. CANOCO reference manual and CanoDraw for Windows user's guide:software for canonical community ordination (version 4.5)[R]. Ithaca, New York:Microcomputer Power, 2002.
Figuerola E L M, Guerrero L D, Rosa S M, et al. Bacterial indicator of agricultural management for soil under no-till crop production[J]. Plos One, 2012,7(11):e51075.
[25]
Balkwill D L, Fredrickson J K, Romine M F. Sphingomonas and related genera[M]. New York:Springer, 2006:605-629.
